1. Field
The present invention relates to a method of building a map of a mobile platform in a dynamic environment, and, more particularly, to a method of building a map of a mobile platform in a dynamic environment and detecting an object using a three-dimensional (3D) camera sensor, e.g., an infrared time of flight (IR TOF) camera sensor, for localization.
2. Description of the Related Art
With the advancement of an intelligent unmanned technology, much research has been made on self-localization. Localization using inertial navigation is used in limited applications, such as airplanes or missiles. With the commercialization of a global positioning system (GPS) utilizing an artificial satellite, the localization technology is being used in various applications and commercially produces huge added value. Since the localization technology does not still exhibit an excellent performance indoors or in downtown areas, however, much research is in progress to find a solution to exhibit an excellent performance in any place. In recent years, the localization technology is loaded in mobile products usable indoors, from which the implementation of various functions and huge added value produced therefrom are expected.
For example, for a robot (a housework helping robot or a public service robot) utilized in various applications in recent years to move self-controllably, it is required to simultaneously perform a localization process to recognize its position without preliminary information on a peripheral environment and a map building process to build a map from the information on the environment, which is called simultaneous localization and mapping (SLAM).
The SLAM is a technology to build a map in real time and recognize a position using an image and a distance sensor. The SLAM is used as an appropriate substitute for indoor localization. In particular, research is being actively made on SLAM using an evidence grid, which has an advantage in that it is possible to express the peripheral environment through the mapping simultaneously with the localization, thereby achieving the detection of an obstacle. Since the SLAM builds map information in a static environment, however, the result is that the map information is distorted in a dynamic environment having a large number of moving objects (for example, human beings), and the performance of the SLAM is deteriorated.